Trends in territory occupancy, distribution and density of the Bearded Vulture<i>Gypaetus barbatus meridionalis</i>in southern Africa
Bibliographic record
Abstract
Summary Territory occupancy, distribution and density of the isolated Bearded Vulture Gypaetus barbatus meridionalis population in the Maloti-Drakensberg mountains of southern Africa were assessed between two time periods - former (1960–1999) and current (2000–2012) - to identify population trends. Overall, 190 territories were recorded of which 109 are currently occupied. The number of occupied breeding territories decreased by a minimum of 32% and a maximum of 51% over the past five decades. Territories located on the periphery of the breeding range were more likely to be abandoned than those in the core. The current population is estimated at a minimum of 352 and a maximum of 390 individuals. The breeding range decreased by 27%, restricting the birds to an estimated area of occupancy of 28,125 km 2 . Breeding densities also decreased by 20%, declining from 4.9 to 3.9 pairs/1,000 km 2 . In both periods, higher densities were recorded in the core of the range. Nests were located about 9.0 km apart, a slight increase from the 7.7 km recorded formerly. Inter-nest distances increased with distance from the core range. Further studies are required to ascertain whether productivity or survival is limiting population growth, and whether anthropogenic influences are resulting in the abandonment of territories in the periphery of the range and the subsequent decline in numbers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".